Hello, I'm
Bridging the gap between raw data and intelligent systems. Specializing in machine learning pipelines, data modeling, and computer science.
My expertise spans machine learning, natural language processing, computer vision, and deep learning & Software Engineering with the Software development life cycle (SDLC).
Currently I am pursing my B.Tech program from KIIT University (2023-2027).
I am a Computer Science student specializing in Artificial Intelligence and Data Analysis.
My work focuses on building intelligent systems, designing machine learning pipelines, and solving real-world problems using structured data-driven approaches.
I have hands-on experience in model development, feature engineering, dataset structuring, and evaluation techniques.
I enjoy transforming raw data into meaningful insights and building scalable AI solutions with practical impact.
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Currently pursuing my degree with a focus on Artificial Intelligence and Data Analysis. Active in building scalable ML solutions.
CGPA: 8.01
Completed higher secondary education with a strong foundation in mathematics and core sciences.
GPA: 3.38 / 4.0
Completed secondary education with top academic performance.
GPA: 3.76 / 4.0
A major, fully-deployed custom web platform hosted on a private subdomain.
Learn MoreComputer vision model to identify and quantify microplastics in environmental samples.
Learn MoreCNN-based image classification pipeline distinguishing real vs AI images.
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Responsive personal portfolio with custom particle animations and dark/light mode.
Learn MoreK-Means clustering and PCA analysis for retail data.
Learn MoreHardware integration for real-time avoidance algorithms.
Learn MoreIntroduction to project management principles and practices.
Learn about DevOps practices and tools for automating workflows on AWS.
Introduction to containerization and orchestration with Docker.
Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and human language. It involves the development of algorithms and models that enable machines to understand, interpret, and generate human language in a meaningful way. NLP combines computational linguistics with machine learning, deep learning, and statistical modeling to process and analyze large volumes of natural language data. Applications of NLP include language translation, sentiment analysis, chatbots, and information retrieval.
Learning about natural language processing techniques and their applications in real-world scenarios.
Transformer models are a type of deep learning architecture that has revolutionized natural language processing and computer vision tasks. They utilize self-attention mechanisms to capture long-range dependencies in data, enabling them to understand context and relationships more effectively than traditional models. Transformer models have been instrumental in advancing the capabilities of AI systems, leading to breakthroughs in language understanding, image recognition, and generative tasks.
Learning about transformer models and their applications in natural language processing and computer vision.
Implemented and evaluated multiple ML algorithms from regression to PCA, including model comparison, data preprocessing, and visualization using Python and Scikit-learn.
Learning about machine learning algorithms and their applications in various domains.
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